diff options
Diffstat (limited to 'src/core/CL/kernels')
10 files changed, 286 insertions, 225 deletions
diff --git a/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp b/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp index f232f6cfc0..e883e8f250 100644 --- a/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp +++ b/src/core/CL/kernels/CLChannelShuffleLayerKernel.cpp @@ -113,21 +113,7 @@ void CLChannelShuffleLayerKernel::configure(const ICLTensor *input, ICLTensor *o build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size)); build_opts.add_option("-DSRC_DIM_Z=" + support::cpp11::to_string(input->info()->dimension(2))); build_opts.add_option("-DLAST_ACCESSED=" + support::cpp11::to_string(std::max(static_cast<int>(channels - vec_size), 0))); - - switch(input->info()->element_size()) - { - case 1: - build_opts.add_option("-DDATA_TYPE=uchar"); - break; - case 2: - build_opts.add_option("-DDATA_TYPE=ushort"); - break; - case 4: - build_opts.add_option("-DDATA_TYPE=uint"); - break; - default: - ARM_COMPUTE_ERROR("Data type not supported"); - } + build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())); // Create kernel std::string kernel_name = "channel_shuffle_" + lower_string(string_from_data_layout(data_layout)); diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp index 42e5fbc8f2..a2f4a913ce 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp @@ -37,13 +37,15 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/quantization/AsymmHelpers.h" -using namespace arm_compute; +namespace arm_compute +{ using namespace arm_compute::misc::shape_calculator; namespace { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, const Size2D dilation) +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D dilation, + const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); @@ -52,7 +54,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LOGISTIC), "For QASYMM8 only logistic, relu, lower bounded relu and lower-upper bounded relu are supported"); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) != 3 || weights->dimension(1) != 3); ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1 || conv_info.stride().first > 3); @@ -74,28 +75,43 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); } - if(output->total_size() != 0) + if(is_qasymm) { - const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); - } + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1); + ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1); - if(is_qasymm) + if(is_data_type_quantized_per_channel(weights->data_type())) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QSYMM8_PER_CHANNEL); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(2) != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(2) != output_shifts->dimension(0)); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0)); + } + } + else { - const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = (output->total_size() != 0) ? output->quantization_info().uniform() : iq_info; + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + } - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - ARM_COMPUTE_UNUSED(multiplier); - ARM_COMPUTE_RETURN_ERROR_ON(multiplier > 1.0f); + if(output->total_size() != 0) + { + const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); } return Status{}; } -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, - GPUTarget gpu_target, std::string &kernel_name, const Size2D dilation) +std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, GPUTarget gpu_target, std::string &kernel_name, const Size2D dilation) { // Output auto inizialitation if not yet initialized const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); @@ -182,9 +198,9 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen } else { - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()); + const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_data_type_quantized_per_channel(weights->data_type()); - kernel_name = is_qasymm ? "dwc_3x3_native_qasymm8" : "depthwise_convolution_3x3"; + kernel_name = is_qasymm ? "dwc_3x3_native_quantized8" : "depthwise_convolution_3x3"; kernel_name += (is_qasymm && is_dot8_supported ? "_dot8" : ""); kernel_name += (is_qasymm ? "_nchw" : ""); @@ -224,23 +240,28 @@ BorderSize CLDepthwiseConvolutionLayer3x3NCHWKernel::border_size() const return _border_size; } -void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) +void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, + const ICLTensor *output_multipliers, const ICLTensor *output_shifts) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, dilation)); - - bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type()); - - _input = input; - _output = output; - _weights = weights; - _biases = biases; - _conv_stride_x = conv_info.stride().first; - _conv_stride_y = conv_info.stride().second; - _conv_pad_left = conv_info.pad_left(); - _conv_pad_top = conv_info.pad_top(); - _border_size = BorderSize(_conv_pad_top, conv_info.pad_right(), conv_info.pad_bottom(), _conv_pad_left); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), + conv_info, depth_multiplier, act_info, dilation, + (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, + (output_shifts != nullptr) ? output_shifts->info() : nullptr)); + + _input = input; + _output = output; + _weights = weights; + _biases = biases; + _conv_stride_x = conv_info.stride().first; + _conv_stride_y = conv_info.stride().second; + _conv_pad_left = conv_info.pad_left(); + _conv_pad_top = conv_info.pad_top(); + _border_size = BorderSize(_conv_pad_top, conv_info.pad_right(), conv_info.pad_bottom(), _conv_pad_left); + _output_multipliers = output_multipliers; + _output_shifts = output_shifts; + _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); // Configure kernel window std::string kernel_name; @@ -260,24 +281,21 @@ void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); - if(is_qasymm) + if(_is_quantized) { const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform(); const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform(); const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform(); - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - + const bool is_quantized_per_channel = is_data_type_quantized_per_channel(weights->info()->data_type()); + const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_quantized_per_channel; build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y)); build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset)); build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset)); build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_info.offset)); build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * iq_info.offset * wq_info.offset)); - build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); - build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); + build_opts.add_option_if(is_quantized_per_channel, "-DPER_CHANNEL_QUANTIZATION"); + build_opts.add_option_if(is_dot8_supported, "-DIS_DOT8"); if(act_info.enabled()) { @@ -293,6 +311,10 @@ void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); } + + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type())); + build_opts.add_option("-DWEIGHTS_PROMOTED_TYPE=" + get_cl_promoted_type_from_data_type(weights->info()->data_type())); } else { @@ -323,12 +345,15 @@ void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, _config_id += support::cpp11::to_string(output->info()->dimension(1)); } -Status CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, const Size2D &dilation) +Status CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, + const Size2D &dilation, const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { std::string kernel_name; - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info, depth_multiplier, gpu_target, kernel_name, dilation).first); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), + conv_info, depth_multiplier, gpu_target, kernel_name, dilation) + .first); return Status{}; } @@ -353,18 +378,28 @@ void CLDepthwiseConvolutionLayer3x3NCHWKernel::run(const Window &window, cl::Com slice_weights.set_dimension_step(Window::DimX, 0); slice_weights.set_dimension_step(Window::DimY, 0); + unsigned int idx = 3 * num_arguments_per_3D_tensor(); + + // Set output multipliers in case of quantized data type + if(_is_quantized) + { + Window slice; + slice.use_tensor_dimensions(_output_multipliers->info()->tensor_shape()); + add_1D_tensor_argument(idx, _output_multipliers, slice); + add_1D_tensor_argument(idx, _output_shifts, slice); + } + // Set biases if(_biases != nullptr) { - unsigned int idx = 3 * num_arguments_per_3D_tensor(); - Window slice_biases; + Window slice_biases; slice_biases.use_tensor_dimensions(_biases->info()->tensor_shape()); add_1D_tensor_argument(idx, _biases, slice_biases); } do { - unsigned int idx = 0; + idx = 0; add_3D_tensor_argument(idx, _input, slice_in); add_3D_tensor_argument(idx, _output, slice_out); add_3D_tensor_argument(idx, _weights, slice_weights); @@ -373,3 +408,4 @@ void CLDepthwiseConvolutionLayer3x3NCHWKernel::run(const Window &window, cl::Com } while(collapsed.slide_window_slice_3D(slice_out) && collapsed_in.slide_window_slice_3D(slice_in)); } +} // namespace arm_compute diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp index b8b144dbfa..d5f37f32ce 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp @@ -41,17 +41,18 @@ namespace arm_compute { namespace { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, const Size2D &dilation) +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation, + const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32, DataType::QASYMM8); - ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::QASYMM8) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) + ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::QASYMM8) + && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LOGISTIC), "For QASYMM8 only logistic, relu, lower bounded relu and lower-upper bounded relu are supported"); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1); // COMPMID-1071 Add depth multiplier support for NHWC ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1); @@ -63,26 +64,47 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const size_t weights_width = 3; const size_t weights_height = 3; + const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape( + *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation); if(is_qasymm) { DepthwiseConvolutionReshapeInfo info; info.c0 = 4; ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(0) / info.c0) != weights_width * weights_height); + + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1); + ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1); + + if(is_data_type_quantized_per_channel(weights->data_type())) + { + ARM_COMPUTE_RETURN_ERROR_ON(output_shape[0] != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(output_shape[0] != output_shifts->dimension(0)); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0)); + } } else { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_RETURN_ERROR_ON((weights->dimension(1) != weights_width) || (weights->dimension(2) != weights_height)); } if(biases != nullptr) { + ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[0]); if(is_qasymm) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); } else { - ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(0)); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); } @@ -91,27 +113,15 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, if(output->total_size() != 0) { - const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape( - *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); } - if(is_qasymm) - { - const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = (output->total_size() != 0) ? output->quantization_info().uniform() : iq_info; - - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - ARM_COMPUTE_UNUSED(multiplier); - ARM_COMPUTE_RETURN_ERROR_ON(multiplier > 1.0f); - } - return Status{}; } std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, - const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, + ITensorInfo *output_multipliers, ITensorInfo *output_shifts) { const size_t weights_width = 3; const size_t weights_height = 3; @@ -144,7 +154,17 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen if(is_qasymm) { - window_changed = update_window_and_padding(win, input_access, output_access); + if((output_multipliers != nullptr) && (output_shifts != nullptr)) + { + AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, num_elems_accessed_per_iteration); + AccessWindowHorizontal output_shifts_access(output_shifts, 0, num_elems_accessed_per_iteration); + window_changed = window_changed || update_window_and_padding(win, input_access, output_access, output_multipliers_access, output_shifts_access); + } + else + { + Status err = ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "output_multipliers and output_shifts must be non-nullptr for quantized input"); + return std::make_pair(err, win); + } } else { @@ -157,7 +177,6 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen AccessWindowHorizontal bias_access(bias, 0, num_elems_accessed_per_iteration); window_changed = window_changed || update_window_and_padding(win, bias_access); } - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; @@ -175,19 +194,26 @@ BorderSize CLDepthwiseConvolutionLayer3x3NHWCKernel::border_size() const return _border_size; } -void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) +void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, + const ICLTensor *output_multipliers, const ICLTensor *output_shifts) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, dilation)); - auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, dilation); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), + conv_info, depth_multiplier, act_info, dilation, + (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, + (output_shifts != nullptr) ? output_shifts->info() : nullptr)); + auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), + conv_info, depth_multiplier, dilation, + (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, + (output_shifts != nullptr) ? output_shifts->info() : nullptr); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - const bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type()); const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1); - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()); + const bool is_quantized_per_channel = is_data_type_quantized_per_channel(weights->info()->data_type()); + const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()) && !is_quantized_per_channel; _input = input; _output = output; @@ -196,16 +222,19 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, _conv_stride_y = conv_info.stride().second; _num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; _num_planes_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1; + _output_multipliers = output_multipliers; + _output_shifts = output_shifts; + _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); // If QASYMM8 and the 8 bit dot product is available, force _num_planes_processed_per_iteration to 1 - if(is_dot8_supported && is_qasymm) + if(is_dot8_supported && _is_quantized) { _num_planes_processed_per_iteration = 1; } - _border_size = BorderSize(is_qasymm && is_stride_1 ? 0 : conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0); + _border_size = BorderSize(_is_quantized && is_stride_1 ? 0 : conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0); - const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : (8 / input->info()->element_size()); + const unsigned int num_elems_accessed_per_iteration = _is_quantized ? 4 : (8 / input->info()->element_size()); CLBuildOptions build_opts; build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); @@ -217,24 +246,19 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); - if(is_qasymm) + if(_is_quantized) { const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform(); const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform(); const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform(); - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1))); build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset)); build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset)); build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_info.offset)); build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * iq_info.offset * wq_info.offset)); - build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); - build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); + build_opts.add_option_if(is_quantized_per_channel, "-DPER_CHANNEL_QUANTIZATION"); + build_opts.add_option_if(is_dot8_supported, "-DIS_DOT8"); if(act_info.enabled()) { @@ -250,6 +274,10 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); } + + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type())); + build_opts.add_option("-DWEIGHTS_PROMOTED_TYPE=" + get_cl_promoted_type_from_data_type(weights->info()->data_type())); } else { @@ -274,9 +302,9 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, std::string kernel_name; // Create kernel - if(is_qasymm) + if(_is_quantized) { - kernel_name = std::string("dwc_3x3_reshaped_qasymm8"); + kernel_name = std::string("dwc_3x3_reshaped_quantized8"); kernel_name += (is_dot8_supported && is_stride_1_dilation_1 ? "_dot8" : ""); kernel_name += (is_stride_1_dilation_1 ? "_stride1" : ""); kernel_name += "_nhwc"; @@ -309,13 +337,16 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, _config_id += string_from_data_type(input->info()->data_type()); } -Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) +Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, + const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, output_multipliers, output_shifts)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), biases != nullptr ? biases->clone().get() : nullptr, - output->clone().get(), conv_info, depth_multiplier, dilation) + output->clone().get(), conv_info, depth_multiplier, dilation, + (output_multipliers != nullptr) ? output_multipliers->clone().get() : nullptr, + (output_shifts != nullptr) ? output_shifts->clone().get() : nullptr) .first); return Status{}; @@ -329,7 +360,6 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com // Collapse window Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); const size_t total_batches = _input->info()->tensor_shape().total_size_upper(3); - const bool is_qasymm = is_data_type_quantized_asymmetric(_input->info()->data_type()); Window win = window_collapsed; win.set(Window::DimZ, Window::Dimension(0, std::ceil(_output->info()->dimension(2) / static_cast<float>(_num_planes_processed_per_iteration)) * total_batches, 1)); @@ -344,7 +374,16 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com Window slice_in = win_in.first_slice_window_4D(); Window slice_out = win.first_slice_window_4D(); - unsigned int idx = 2 * num_arguments_per_4D_tensor() + (is_qasymm ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor()); + unsigned int idx = 2 * num_arguments_per_4D_tensor() + (_is_quantized ? num_arguments_per_2D_tensor() : num_arguments_per_3D_tensor()); + + if(_is_quantized) + { + Window slice; + slice.use_tensor_dimensions(_output_multipliers->info()->tensor_shape()); + slice.set_dimension_step(Window::DimX, window.x().step()); + add_1D_tensor_argument(idx, _output_multipliers, slice); + add_1D_tensor_argument(idx, _output_shifts, slice); + } if(_biases != nullptr) { @@ -398,7 +437,7 @@ void CLDepthwiseConvolutionLayer3x3NHWCKernel::run(const Window &window, cl::Com unsigned int idx = 0; add_4D_tensor_argument(idx, _input, slice_in); add_4D_tensor_argument(idx, _output, slice_out); - if(is_qasymm) + if(_is_quantized) { add_2D_tensor_argument(idx, _weights, slice_out); } diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp index 2115fc614d..3fc236eaa7 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp @@ -42,13 +42,13 @@ namespace arm_compute namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info, - const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, + const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { ARM_COMPUTE_UNUSED(dwc_info); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1 && dwc_weights_info.n0 != 1); ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1); ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().second < 1); @@ -57,24 +57,53 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, ARM_COMPUTE_UNUSED(idx_c); ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_c) != (input->dimension(idx_c) * depth_multiplier)); + const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); + + const bool is_quantized = is_data_type_quantized(input->data_type()); + if(biases != nullptr) { - ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[idx_c]); ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); - if(is_data_type_quantized(input->data_type())) + if(is_quantized) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32); } else { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases); + } + } + + if(is_quantized) + { + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32); + ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1); + ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1); + + if(is_data_type_quantized_per_channel(weights->data_type())) + { + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QSYMM8_PER_CHANNEL); + ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_shifts->dimension(0)); + } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0)); } } + else + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + } if(output->total_size() != 0) { - const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape); } @@ -82,7 +111,8 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, } std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info, - const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, + ITensorInfo *output_multipliers, ITensorInfo *output_shifts) { ARM_COMPUTE_UNUSED(dwc_info); @@ -113,6 +143,21 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen window_changed = update_window_and_padding(win, input_access, weights_access, output_access); } + if(is_data_type_quantized(input->data_type())) + { + if((output_multipliers != nullptr) && (output_shifts != nullptr)) + { + AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, n0); + AccessWindowHorizontal output_shifts_access(output_shifts, 0, n0); + window_changed = window_changed || update_window_and_padding(win, output_multipliers_access, output_shifts_access); + } + else + { + Status err = ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "output_multipliers and output_shifts must be non-nullptr for quantized input"); + return std::make_pair(err, win); + } + } + output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; @@ -121,32 +166,44 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITen } // namespace CLDepthwiseConvolutionLayerNativeKernel::CLDepthwiseConvolutionLayerNativeKernel() - : _input(nullptr), _weights(nullptr), _biases(nullptr), _output(nullptr), _depth_multiplier(1) + : _input(nullptr), + _weights(nullptr), + _biases(nullptr), + _output(nullptr), + _depth_multiplier(1), + _output_multipliers(nullptr), + _output_shifts(nullptr), + _is_quantized(false) { } void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCWeightsKernelInfo &dwc_weights_info, - const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation, + const ICLTensor *output_multipliers, const ICLTensor *output_shifts) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, - dilation)); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), + dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, + (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr)); - auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, - dilation); + auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), + dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, + (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - _input = input; - _output = output; - _weights = weights; - _biases = biases; - _depth_multiplier = depth_multiplier; + _input = input; + _output = output; + _weights = weights; + _biases = biases; + _depth_multiplier = depth_multiplier; + _output_multipliers = output_multipliers; + _output_shifts = output_shifts; + _is_quantized = is_data_type_quantized(input->info()->data_type()); const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH); const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); const size_t weights_width = weights->info()->dimension(idx_w); const size_t weights_height = weights->info()->dimension(idx_h); - const bool is_quantized = is_data_type_quantized(input->info()->data_type()); CLBuildOptions build_opts; build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); @@ -166,24 +223,18 @@ void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x())); build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y())); - std::string kernel_name = (is_quantized) ? "dwc_MxN_native_quantized8_nhwc" : "dwc_MxN_native_fp_nhwc"; + std::string kernel_name = (_is_quantized) ? "dwc_MxN_native_quantized8_nhwc" : "dwc_MxN_native_fp_nhwc"; - if(is_quantized) + if(_is_quantized) { const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform(); const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform(); const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform(); - float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset)); build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset)); build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_info.offset)); - build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier)); - build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift)); + build_opts.add_option_if(is_data_type_quantized_per_channel(weights->info()->data_type()), "-DPER_CHANNEL_QUANTIZATION"); if(dwc_info.activation_info.enabled()) { @@ -199,6 +250,9 @@ void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1)); build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1)); } + + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type())); } else { @@ -228,12 +282,15 @@ void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, } Status CLDepthwiseConvolutionLayerNativeKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, - const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation) + const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const Size2D &dilation, const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts) { - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, output_multipliers, output_shifts)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), biases != nullptr ? biases->clone().get() : nullptr, - output->clone().get(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation) + output->clone().get(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, + output_multipliers != nullptr ? output_multipliers->clone().get() : nullptr, + output_shifts != nullptr ? output_shifts->clone().get() : nullptr) .first); return Status{}; @@ -255,15 +312,23 @@ void CLDepthwiseConvolutionLayerNativeKernel::run(const Window &window, cl::Comm slice_out.set(Window::DimX, Window::Dimension(0, _input->info()->tensor_shape()[0], 1)); } + unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor(); + + // Set output multipliers in case of quantized data type + if(_is_quantized) + { + add_1D_tensor_argument(idx, _output_multipliers, slice_in); + add_1D_tensor_argument(idx, _output_shifts, slice_in); + } + if(_biases != nullptr) { - unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor(); add_1D_tensor_argument(idx, _biases, slice_in); } do { - unsigned int idx = 0; + idx = 0; add_4D_tensor_argument(idx, _input, slice_in); add_4D_tensor_argument(idx, _output, slice_out); add_3D_tensor_argument(idx, _weights, slice_out); diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp index 1fd6312295..ec889ec949 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.cpp @@ -47,7 +47,6 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC); ARM_COMPUTE_RETURN_ERROR_ON(info.c0 != 4); ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(idx_h) != 3); @@ -98,10 +97,10 @@ void CLDepthwiseConvolutionLayerReshapeWeightsKernel::configure(const ICLTensor // Build the kernel CLBuildOptions build_opts; - build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type())); build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(info.c0)); build_opts.add_option("-DDST_WIDTH=" + support::cpp11::to_string(_output->info()->dimension(0))); build_opts.add_option_if(info.transpose, "-DTRANSPOSE"); + build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())); _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("depthwise_convolution_reshape_weights", build_opts.options())); } diff --git a/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp b/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp index 72f2ca40f5..7010dffd25 100644 --- a/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp +++ b/src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.cpp @@ -37,7 +37,8 @@ #include "arm_compute/core/Window.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" -using namespace arm_compute; +namespace arm_compute +{ using namespace arm_compute::misc::shape_calculator; namespace @@ -139,21 +140,7 @@ void CLGEMMReshapeLHSMatrixKernel::configure(const ICLTensor *input, ICLTensor * build_opts.add_option_if(_reinterpret_input_as_3d, "-DREINTERPRET_INPUT_AS_3D"); build_opts.add_option_if(_reinterpret_input_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(1))); build_opts.add_option_if(_reinterpret_input_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(input->info()->dimension(2))); - - switch(input->info()->element_size()) - { - case 1: - build_opts.add_option("-DDATA_TYPE=uchar"); - break; - case 2: - build_opts.add_option("-DDATA_TYPE=ushort"); - break; - case 4: - build_opts.add_option("-DDATA_TYPE=uint"); - break; - default: - ARM_COMPUTE_ERROR("Data type not supported"); - } + build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())); std::string kernel_name("gemm_reshape_lhs_matrix_"); kernel_name += lhs_info.transpose ? "t" : "nt"; @@ -219,4 +206,5 @@ void CLGEMMReshapeLHSMatrixKernel::run(const Window &window, cl::CommandQueue &q enqueue(queue, *this, slice, lws_hint()); } while(window.slide_window_slice_3D(slice)); -}
\ No newline at end of file +} +} // namespace arm_compute
\ No newline at end of file diff --git a/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp b/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp index 2ca4132b15..6f6019d26a 100644 --- a/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp +++ b/src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.cpp @@ -37,7 +37,8 @@ #include "arm_compute/core/Window.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" -using namespace arm_compute; +namespace arm_compute +{ using namespace arm_compute::misc::shape_calculator; namespace @@ -118,21 +119,7 @@ void CLGEMMReshapeRHSMatrixKernel::configure(const ICLTensor *input, ICLTensor * build_opts.add_option_if(rhs_info.transpose, "-DTRANSPOSE"); build_opts.add_option_if(rhs_info.interleave, "-DINTERLEAVE"); build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input->info()->dimension(1))); - - switch(input->info()->element_size()) - { - case 1: - build_opts.add_option("-DDATA_TYPE=uchar"); - break; - case 2: - build_opts.add_option("-DDATA_TYPE=ushort"); - break; - case 4: - build_opts.add_option("-DDATA_TYPE=uint"); - break; - default: - ARM_COMPUTE_ERROR("Data type not supported"); - } + build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())); std::string kernel_name("gemm_reshape_rhs_matrix_"); kernel_name += rhs_info.transpose ? "t" : "nt"; @@ -169,4 +156,5 @@ void CLGEMMReshapeRHSMatrixKernel::run(const Window &window, cl::CommandQueue &q enqueue(queue, *this, slice, lws_hint()); } while(window.slide_window_slice_3D(slice)); -}
\ No newline at end of file +} +} // namespace arm_compute
\ No newline at end of file diff --git a/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp b/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp index ea292c0b7b..85917d38dd 100644 --- a/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp +++ b/src/core/CL/kernels/CLHeightConcatenateLayerKernel.cpp @@ -40,7 +40,8 @@ #include <map> -using namespace arm_compute; +namespace arm_compute +{ namespace { std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, unsigned int height_offset, ITensorInfo *output, unsigned int &num_elems_processed_per_iteration) @@ -102,31 +103,7 @@ void CLHeightConcatenateLayerKernel::configure(const ICLTensor *input, unsigned // Add build options CLBuildOptions build_opts; - - switch(input->info()->element_size()) - { - case 1: - { - build_opts.add_option("-DDATA_TYPE=uchar"); - break; - } - case 2: - { - build_opts.add_option("-DDATA_TYPE=short"); - break; - } - case 4: - { - build_opts.add_option("-DDATA_TYPE=int"); - break; - } - default: - { - ARM_COMPUTE_ERROR("Unsupported input data type."); - break; - } - } - + build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())); build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(_num_elems_processed_per_iteration)); build_opts.add_option("-DHEIGHT_OFFSET=" + support::cpp11::to_string(_height_offset)); build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(input->info()->dimension(2))); @@ -164,3 +141,4 @@ void CLHeightConcatenateLayerKernel::run(const Window &window, cl::CommandQueue add_4D_tensor_argument(idx, _output, window); enqueue(queue, *this, window, lws_hint()); } +} // namespace arm_compute diff --git a/src/core/CL/kernels/CLPermuteKernel.cpp b/src/core/CL/kernels/CLPermuteKernel.cpp index 9cb72b3c04..81a810fcb8 100644 --- a/src/core/CL/kernels/CLPermuteKernel.cpp +++ b/src/core/CL/kernels/CLPermuteKernel.cpp @@ -52,11 +52,6 @@ TensorShape get_output_shape(const ITensorInfo *input, const PermutationVector & Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PermutationVector &perm) { ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8, DataType::S8, DataType::QASYMM8, - DataType::U16, DataType::S16, - DataType::U32, DataType::S32, - DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() < 1 || input->num_dimensions() > 4, "Permutation upto 4-D input tensor is supported"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(perm.num_dimensions() < 1 || perm.num_dimensions() > 4, diff --git a/src/core/CL/kernels/CLReverseKernel.cpp b/src/core/CL/kernels/CLReverseKernel.cpp index 84bf5bf874..796f0d068a 100644 --- a/src/core/CL/kernels/CLReverseKernel.cpp +++ b/src/core/CL/kernels/CLReverseKernel.cpp @@ -81,20 +81,7 @@ void CLReverseKernel::configure(const ICLTensor *input, ICLTensor *output, const // Set kernel build options CLBuildOptions build_opts; build_opts.add_option("-DNUM_REVERSE_DIMS=" + support::cpp11::to_string(axis->info()->dimension(0))); - switch(input->info()->element_size()) - { - case 1: - build_opts.add_option("-DDATA_TYPE=uchar"); - break; - case 2: - build_opts.add_option("-DDATA_TYPE=ushort"); - break; - case 4: - build_opts.add_option("-DDATA_TYPE=uint"); - break; - default: - ARM_COMPUTE_ERROR("Data type not supported"); - } + build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(input->info()->element_size())); // Create kernel _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("reverse", build_opts.options())); |